Privacy in Statistical Databases

Table of Contents

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   Book Overview
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   Chapter 1 An Optimization-Based Decomposition Heuristic for the Microaggregation Problem
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   Chapter 2 Privacy Analysis with a Distributed Transition System and a Data-Wise Metric
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   Chapter 3 Multivariate Mean Comparison Under Differential Privacy
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   Chapter 4 Asking the Proper Question: Adjusting Queries to Statistical Procedures Under Differential Privacy
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   Chapter 5 Towards Integrally Private Clustering: Overlapping Clusters for High Privacy Guarantees
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   Chapter 6 Perspectives for Tabular Data Protection – How About Synthetic Data?
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   Chapter 7 On Privacy of Multidimensional Data Against Aggregate Knowledge Attacks
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   Chapter 8 Synthetic Decimal Numbers as a Flexible Tool for Suppression of Post-published Tabular Data
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    Chapter 9 The Risk of Disclosure When Reporting Commonly Used Univariate Statistics
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    Chapter 10 Tit-for-Tat Disclosure of a Binding Sequence of User Analyses in Safe Data Access Centers
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    Chapter 11 Secure and Non-interactive k -NN Classifier Using Symmetric Fully Homomorphic Encryption
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    Chapter 12 Automatic Evaluation of Disclosure Risks of Text Anonymization Methods
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    Chapter 13 Generation of Synthetic Trajectory Microdata from Language Models
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    Chapter 14 Synthetic Individual Income Tax Data: Methodology, Utility, and Privacy Implications
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    Chapter 15 On Integrating the Number of Synthetic Data Sets m into the  a priori Synthesis Approach
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    Chapter 16 Challenges in Measuring Utility for Fully Synthetic Data
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    Chapter 17 Comparing the Utility and Disclosure Risk of Synthetic Data with Samples of Microdata
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    Chapter 18 Utility and Disclosure Risk for Differentially Private Synthetic Categorical Data
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    Chapter 19 Membership Inference Attack Against Principal Component Analysis
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    Chapter 20 When Machine Learning Models Leak: An Exploration of Synthetic Training Data
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    Chapter 21 A Note on the Misinterpretation of the US Census Re-identification Attack
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    Chapter 22 A Re-examination of the Census Bureau Reconstruction and Reidentification Attack
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    Chapter 23 Quality Assessment of the 2014 to 2019 National Survey on Drug Use and Health (NSDUH) Public Use Files
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    Chapter 24 Privacy in Practice: Latest Achievements of the Eustat SDC Group
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    Chapter 25 How Adversarial Assumptions Influence Re-identification Risk Measures: A COVID-19 Case Study